Analysis of Biological Networks

By Björn H. Junker, Falk Schreiber. 2008

492 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/0c71f0880a11f961014f31e0c5ed43b57c9d7df1

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In Computational Theory and Mathematics

In Molecular Biology

Citations in the corpus

Recent Advances in Graph Partitioning (2013, unknown): “For details see [JS08, Mon10].”
On the use of correlation as a measure of network connectivity (2012, methodology): “…functional brain networks, our conclusions and methods also apply to metabolite, protein and gene correlation networks (Gillis and Pavlidis, 2011; Junker and Schreiber, 2008), financial portfolio networks (Hirschberger et al., 2004) and anatomical brain networks inwhich connectivity ismeasured…”
Modelling transmission and control of the COVID-19 pandemic in Australia (2020, background): “ thresholds for possible emergence of new strains, as well as various \change points" in the spreading rate [33, 34, 28, 35], studies of genomic surveillance data interpreted as complex networks [36, 37, 38, 39, 40], dynamic models of social behaviour in times of health crises [41, 15, 42, 43, ”
NetCoMi: network construction and comparison for microbiome data in R (2020, unknown): “Average path length Arithmetic mean of all shortest paths between vertices in a network [83].”
Metagenomic and network analysis reveal wide distribution and co-occurrence of environmental antibiotic resistance genes (2015, unknown): “01 (Junker and Schreiber, 2008).”
Using graph theory to analyze biological networks (2011, background): “The nodes with the highest centralities in such networks correspond to domains involved in signal transduction and cell-cell contacts [164].”
Centrality Analysis Methods for Biological Networks and Their Application to Gene Regulatory Networks (2008, methodology): “To investigate these complex and large networks different network analysis methods have been developed or employed from other ﬁ elds of sciences (Junker and Schreiber (2008)).”
Community detection in graphs (2009, background): “(GRN) and metabolic networks (MN) are meanwhile standard objects of investigation in biology and bioinformatics [429].”
Online Factorization and Partition of Complex Networks From Random Walks (2017, unknown): “Examples include protein-protein interaction networks [9], phone communication networks [15], collaboration networks [4], and the gravitational interaction network of dark matter particles in cosmology [17, 12, 14].”
Studying protein^protein interaction networks: a systems view on diseases (2012, background): “An example of this is the gene regulation networks and a great deal is known about their structural organization [29–31].”
Adaptation, Learning, and Optimization over Networks (2014, background): “They are also well-suited to model several forms of complex behavior exhibited by biological [16, 50, 131, 147] and social networks [15, 77, 92, 121, 230] such as fish schooling [188], prey-predator maneuvers [105, 171], bird formations [110, 119], bee swarming [12, 22, 125, 220], bacteria motility ”